Overview

Dataset statistics

Number of variables26
Number of observations96844
Missing cells162203
Missing cells (%)6.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.2 MiB
Average record size in memory208.0 B

Variable types

Text10
Unsupported9
DateTime1
Categorical5
Numeric1

Alerts

Tipo_restos is highly imbalanced (82.7%)Imbalance
Conocido_desconocido is highly imbalanced (55.8%)Imbalance
Primer_apellido has 1878 (1.9%) missing valuesMissing
Nombres_propios has 2095 (2.2%) missing valuesMissing
Procedencia_alcaldia has 31946 (33.0%) missing valuesMissing
Procedencia_acta has 25635 (26.5%) missing valuesMissing
Diagnostico_estandar has 8267 (8.5%) missing valuesMissing
Diagnostico_extendido has 8267 (8.5%) missing valuesMissing
Observaciones has 82723 (85.4%) missing valuesMissing
ID has unique valuesUnique
Numero_progresivo_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Fecha_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Expediente_SEMEFO_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Procedencia_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Numero_acta_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Procedencia_acta is an unsupported type, check if it needs cleaning or further analysisUnsupported
Edad_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Foja_transcrito is an unsupported type, check if it needs cleaning or further analysisUnsupported
Observaciones is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2025-02-12 02:01:12.334692
Analysis finished2025-02-12 02:01:19.037178
Duration6.7 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

ID
Text

UNIQUE 

Distinct96844
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
2025-02-11T20:01:19.151093image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters1258972
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96844 ?
Unique (%)100.0%

Sample

1st rowBO_1968_00001
2nd rowBO_1968_00002
3rd rowBO_1968_00003
4th rowBO_1968_00004
5th rowBO_1968_00005
ValueCountFrequency (%)
bo_1968_00001 1
 
< 0.1%
bo_1968_00015 1
 
< 0.1%
bo_1968_00006 1
 
< 0.1%
bo_1968_00007 1
 
< 0.1%
bo_1968_00008 1
 
< 0.1%
bo_1968_00009 1
 
< 0.1%
bo_1968_00010 1
 
< 0.1%
bo_1968_00011 1
 
< 0.1%
bo_1968_00046 1
 
< 0.1%
bo_1968_00012 1
 
< 0.1%
Other values (96834) 96834
> 99.9%
2025-02-11T20:01:19.344955image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 193688
15.4%
1 154647
12.3%
0 154514
12.3%
9 137570
10.9%
7 102548
8.1%
B 96844
7.7%
O 96844
7.7%
8 62974
 
5.0%
2 57774
 
4.6%
6 53714
 
4.3%
Other values (3) 147855
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 871596
69.2%
Connector Punctuation 193688
 
15.4%
Uppercase Letter 193688
 
15.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 154647
17.7%
0 154514
17.7%
9 137570
15.8%
7 102548
11.8%
8 62974
7.2%
2 57774
 
6.6%
6 53714
 
6.2%
3 50864
 
5.8%
4 49755
 
5.7%
5 47236
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
B 96844
50.0%
O 96844
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 193688
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1065284
84.6%
Latin 193688
 
15.4%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 193688
18.2%
1 154647
14.5%
0 154514
14.5%
9 137570
12.9%
7 102548
9.6%
8 62974
 
5.9%
2 57774
 
5.4%
6 53714
 
5.0%
3 50864
 
4.8%
4 49755
 
4.7%
Latin
ValueCountFrequency (%)
B 96844
50.0%
O 96844
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1258972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 193688
15.4%
1 154647
12.3%
0 154514
12.3%
9 137570
10.9%
7 102548
8.1%
B 96844
7.7%
O 96844
7.7%
8 62974
 
5.0%
2 57774
 
4.6%
6 53714
 
4.3%
Other values (3) 147855
11.7%

Numero_progresivo_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Nombre_completo_transcrito
Text

Distinct75516
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
2025-02-11T20:01:19.513421image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length132
Median length48
Mean length22.59474
Min length1

Characters and Unicode

Total characters2188165
Distinct characters61
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73906 ?
Unique (%)76.3%

Sample

1st rowacosta ortega teresa
2nd rowavila de cuestas catalina
3rd rowarzate paredes juan
4th rowalvarez martinez isaac
5th rowarellano viuda de campos ma.
ValueCountFrequency (%)
desconocido 13187
 
4.2%
de 9468
 
3.0%
hernandez 5847
 
1.9%
garcia 4946
 
1.6%
martinez 4625
 
1.5%
con 4320
 
1.4%
jose 4266
 
1.4%
gonzalez 3775
 
1.2%
lopez 3316
 
1.1%
sanchez 3077
 
1.0%
Other values (14220) 257038
81.9%
2025-02-11T20:01:19.741770image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 247825
11.3%
217022
 
9.9%
e 213704
 
9.8%
o 202460
 
9.3%
r 168328
 
7.7%
n 140674
 
6.4%
i 132017
 
6.0%
c 103482
 
4.7%
l 102371
 
4.7%
d 97298
 
4.4%
Other values (51) 562984
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1935397
88.4%
Space Separator 217022
 
9.9%
Uppercase Letter 17266
 
0.8%
Other Punctuation 11718
 
0.5%
Decimal Number 6511
 
0.3%
Open Punctuation 102
 
< 0.1%
Close Punctuation 100
 
< 0.1%
Dash Punctuation 48
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 247825
12.8%
e 213704
11.0%
o 202460
10.5%
r 168328
 
8.7%
n 140674
 
7.3%
i 132017
 
6.8%
c 103482
 
5.3%
l 102371
 
5.3%
d 97298
 
5.0%
s 92146
 
4.8%
Other values (18) 435092
22.5%
Uppercase Letter
ValueCountFrequency (%)
I 2158
12.5%
P 2158
12.5%
A 2158
12.5%
G 2158
12.5%
T 2158
12.5%
L 2158
12.5%
S 2158
12.5%
N 2158
12.5%
E 1
 
< 0.1%
B 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
. 10307
88.0%
" 1031
 
8.8%
' 333
 
2.8%
: 23
 
0.2%
, 10
 
0.1%
/ 5
 
< 0.1%
? 4
 
< 0.1%
# 4
 
< 0.1%
* 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 4322
66.4%
6 2158
33.1%
2 14
 
0.2%
3 11
 
0.2%
4 3
 
< 0.1%
5 2
 
< 0.1%
0 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 89
89.0%
] 11
 
11.0%
Open Punctuation
ValueCountFrequency (%)
( 89
87.3%
[ 13
 
12.7%
Space Separator
ValueCountFrequency (%)
217022
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1952663
89.2%
Common 235502
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 247825
12.7%
e 213704
10.9%
o 202460
10.4%
r 168328
 
8.6%
n 140674
 
7.2%
i 132017
 
6.8%
c 103482
 
5.3%
l 102371
 
5.2%
d 97298
 
5.0%
s 92146
 
4.7%
Other values (28) 452358
23.2%
Common
ValueCountFrequency (%)
217022
92.2%
. 10307
 
4.4%
1 4322
 
1.8%
6 2158
 
0.9%
" 1031
 
0.4%
' 333
 
0.1%
) 89
 
< 0.1%
( 89
 
< 0.1%
- 48
 
< 0.1%
: 23
 
< 0.1%
Other values (13) 80
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2183846
99.8%
None 4319
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 247825
11.3%
217022
 
9.9%
e 213704
 
9.8%
o 202460
 
9.3%
r 168328
 
7.7%
n 140674
 
6.4%
i 132017
 
6.0%
c 103482
 
4.7%
l 102371
 
4.7%
d 97298
 
4.5%
Other values (49) 558665
25.6%
None
ValueCountFrequency (%)
í 4316
99.9%
ñ 3
 
0.1%

Primer_apellido
Text

MISSING 

Distinct7797
Distinct (%)8.2%
Missing1878
Missing (%)1.9%
Memory size756.7 KiB
2025-02-11T20:01:19.942861image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length29
Median length26
Mean length6.0098983
Min length1

Characters and Unicode

Total characters570736
Distinct characters36
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5370 ?
Unique (%)5.7%

Sample

1st rowacosta
2nd rowavila
3rd rowarzate
4th rowalvarez
5th rowarellano
ValueCountFrequency (%)
s-d 18107
 
18.5%
hernandez 2961
 
3.0%
garcia 2577
 
2.6%
martinez 2353
 
2.4%
gonzalez 1934
 
2.0%
lopez 1694
 
1.7%
sanchez 1583
 
1.6%
rodriguez 1480
 
1.5%
perez 1407
 
1.4%
ramirez 1402
 
1.4%
Other values (7084) 62188
63.7%
2025-02-11T20:01:20.188699image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 75980
13.3%
e 60221
10.6%
r 54691
 
9.6%
s 41022
 
7.2%
o 40128
 
7.0%
d 35235
 
6.2%
n 34549
 
6.1%
z 32630
 
5.7%
i 28647
 
5.0%
l 28102
 
4.9%
Other values (26) 139531
24.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 549554
96.3%
Dash Punctuation 18109
 
3.2%
Space Separator 2728
 
0.5%
Other Punctuation 338
 
0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 75980
13.8%
e 60221
11.0%
r 54691
10.0%
s 41022
 
7.5%
o 40128
 
7.3%
d 35235
 
6.4%
n 34549
 
6.3%
z 32630
 
5.9%
i 28647
 
5.2%
l 28102
 
5.1%
Other values (17) 118349
21.5%
Other Punctuation
ValueCountFrequency (%)
. 217
64.2%
" 118
34.9%
' 3
 
0.9%
Dash Punctuation
ValueCountFrequency (%)
- 18109
100.0%
Space Separator
ValueCountFrequency (%)
2728
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 3
100.0%
Close Punctuation
ValueCountFrequency (%)
] 2
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 549554
96.3%
Common 21182
 
3.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 75980
13.8%
e 60221
11.0%
r 54691
10.0%
s 41022
 
7.5%
o 40128
 
7.3%
d 35235
 
6.4%
n 34549
 
6.3%
z 32630
 
5.9%
i 28647
 
5.2%
l 28102
 
5.1%
Other values (17) 118349
21.5%
Common
ValueCountFrequency (%)
- 18109
85.5%
2728
 
12.9%
. 217
 
1.0%
" 118
 
0.6%
[ 3
 
< 0.1%
' 3
 
< 0.1%
] 2
 
< 0.1%
+ 1
 
< 0.1%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 570735
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 75980
13.3%
e 60221
10.6%
r 54691
 
9.6%
s 41022
 
7.2%
o 40128
 
7.0%
d 35235
 
6.2%
n 34549
 
6.1%
z 32630
 
5.7%
i 28647
 
5.0%
l 28102
 
4.9%
Other values (25) 139530
24.4%
None
ValueCountFrequency (%)
ñ 1
100.0%

Segundo_apellido
Text

Distinct8317
Distinct (%)8.6%
Missing281
Missing (%)0.3%
Memory size756.7 KiB
2025-02-11T20:01:20.366306image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length25
Median length23
Mean length5.9092717
Min length1

Characters and Unicode

Total characters570617
Distinct characters39
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5633 ?
Unique (%)5.8%

Sample

1st rowortega
2nd rowde cuestas
3rd rowparedes
4th rowmartinez
5th rowviuda de campos
ValueCountFrequency (%)
s-d 21916
 
21.6%
de 3109
 
3.1%
hernandez 2881
 
2.8%
garcia 2366
 
2.3%
martinez 2263
 
2.2%
gonzalez 1839
 
1.8%
lopez 1613
 
1.6%
sanchez 1495
 
1.5%
rodriguez 1398
 
1.4%
perez 1344
 
1.3%
Other values (6954) 61156
60.3%
2025-02-11T20:01:20.576138image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 73198
12.8%
e 59670
10.5%
r 52015
 
9.1%
s 43698
 
7.7%
d 40930
 
7.2%
o 38814
 
6.8%
n 33651
 
5.9%
z 31111
 
5.5%
i 27957
 
4.9%
l 26826
 
4.7%
Other values (29) 142747
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 542311
95.0%
Dash Punctuation 21917
 
3.8%
Space Separator 4817
 
0.8%
Other Punctuation 1555
 
0.3%
Close Punctuation 8
 
< 0.1%
Open Punctuation 8
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 73198
13.5%
e 59670
11.0%
r 52015
9.6%
s 43698
 
8.1%
d 40930
 
7.5%
o 38814
 
7.2%
n 33651
 
6.2%
z 31111
 
5.7%
i 27957
 
5.2%
l 26826
 
4.9%
Other values (17) 114441
21.1%
Other Punctuation
ValueCountFrequency (%)
. 817
52.5%
" 542
34.9%
' 194
 
12.5%
, 1
 
0.1%
? 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
] 4
50.0%
) 4
50.0%
Open Punctuation
ValueCountFrequency (%)
( 4
50.0%
[ 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 21917
100.0%
Space Separator
ValueCountFrequency (%)
4817
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 542311
95.0%
Common 28306
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 73198
13.5%
e 59670
11.0%
r 52015
9.6%
s 43698
 
8.1%
d 40930
 
7.5%
o 38814
 
7.2%
n 33651
 
6.2%
z 31111
 
5.7%
i 27957
 
5.2%
l 26826
 
4.9%
Other values (17) 114441
21.1%
Common
ValueCountFrequency (%)
- 21917
77.4%
4817
 
17.0%
. 817
 
2.9%
" 542
 
1.9%
' 194
 
0.7%
] 4
 
< 0.1%
( 4
 
< 0.1%
) 4
 
< 0.1%
[ 4
 
< 0.1%
0 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 570615
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 73198
12.8%
e 59670
10.5%
r 52015
 
9.1%
s 43698
 
7.7%
d 40930
 
7.2%
o 38814
 
6.8%
n 33651
 
5.9%
z 31111
 
5.5%
i 27957
 
4.9%
l 26826
 
4.7%
Other values (28) 142745
25.0%
None
ValueCountFrequency (%)
ñ 2
100.0%

Nombres_propios
Text

MISSING 

Distinct7777
Distinct (%)8.2%
Missing2095
Missing (%)2.2%
Memory size756.7 KiB
2025-02-11T20:01:20.753875image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length55
Median length30
Mean length6.3480037
Min length1

Characters and Unicode

Total characters601467
Distinct characters46
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5504 ?
Unique (%)5.8%

Sample

1st rowteresa
2nd rowcatalina
3rd rowjuan
4th rowisaac
5th rowma.
ValueCountFrequency (%)
s-d 18138
 
16.8%
jose 4193
 
3.9%
maria 2661
 
2.5%
juan 2414
 
2.2%
luis 2160
 
2.0%
jesus 1780
 
1.7%
antonio 1757
 
1.6%
francisco 1667
 
1.5%
manuel 1518
 
1.4%
j 1497
 
1.4%
Other values (3884) 70047
65.0%
2025-02-11T20:01:20.968348image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 72452
12.0%
o 55652
 
9.3%
e 51934
 
8.6%
i 46914
 
7.8%
s 46171
 
7.7%
r 45752
 
7.6%
n 37381
 
6.2%
d 36321
 
6.0%
l 34313
 
5.7%
u 23464
 
3.9%
Other values (36) 151113
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 565653
94.0%
Dash Punctuation 18142
 
3.0%
Space Separator 13088
 
2.2%
Other Punctuation 4550
 
0.8%
Close Punctuation 13
 
< 0.1%
Open Punctuation 13
 
< 0.1%
Decimal Number 6
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 72452
12.8%
o 55652
9.8%
e 51934
9.2%
i 46914
8.3%
s 46171
8.2%
r 45752
 
8.1%
n 37381
 
6.6%
d 36321
 
6.4%
l 34313
 
6.1%
u 23464
 
4.1%
Other values (16) 115299
20.4%
Other Punctuation
ValueCountFrequency (%)
. 4361
95.8%
" 170
 
3.7%
' 9
 
0.2%
, 6
 
0.1%
/ 2
 
< 0.1%
* 1
 
< 0.1%
: 1
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
3 2
33.3%
2 1
16.7%
1 1
16.7%
7 1
16.7%
8 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 8
61.5%
] 5
38.5%
Open Punctuation
ValueCountFrequency (%)
( 8
61.5%
[ 5
38.5%
Uppercase Letter
ValueCountFrequency (%)
E 1
50.0%
B 1
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 18142
100.0%
Space Separator
ValueCountFrequency (%)
13088
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 565655
94.0%
Common 35812
 
6.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 72452
12.8%
o 55652
9.8%
e 51934
9.2%
i 46914
8.3%
s 46171
8.2%
r 45752
 
8.1%
n 37381
 
6.6%
d 36321
 
6.4%
l 34313
 
6.1%
u 23464
 
4.1%
Other values (18) 115301
20.4%
Common
ValueCountFrequency (%)
- 18142
50.7%
13088
36.5%
. 4361
 
12.2%
" 170
 
0.5%
' 9
 
< 0.1%
) 8
 
< 0.1%
( 8
 
< 0.1%
, 6
 
< 0.1%
] 5
 
< 0.1%
[ 5
 
< 0.1%
Other values (8) 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 601467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 72452
12.0%
o 55652
 
9.3%
e 51934
 
8.6%
i 46914
 
7.8%
s 46171
 
7.7%
r 45752
 
7.6%
n 37381
 
6.2%
d 36321
 
6.0%
l 34313
 
5.7%
u 23464
 
3.9%
Other values (36) 151113
25.1%

Fecha_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Fecha_estandar
Date

Distinct5479
Distinct (%)5.7%
Missing266
Missing (%)0.3%
Memory size756.7 KiB
Minimum1968-01-01 00:00:00
Maximum1982-12-31 00:00:00
2025-02-11T20:01:21.034512image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2025-02-11T20:01:21.088652image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Expediente_SEMEFO_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Procedencia_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Procedencia_estandar
Text

Distinct109
Distinct (%)0.1%
Missing408
Missing (%)0.4%
Memory size756.7 KiB
2025-02-11T20:01:21.194201image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.9963499
Min length2

Characters and Unicode

Total characters288956
Distinct characters40
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS-D
2nd rowS-D
3rd rowS-D
4th rowS-D
5th rowS-D
ValueCountFrequency (%)
s-d 26833
27.8%
32a 3635
 
3.8%
33a 3054
 
3.2%
37a 2812
 
2.9%
1a 2445
 
2.5%
htb 2294
 
2.4%
20a 2254
 
2.3%
13a 2136
 
2.2%
35a 2063
 
2.1%
36a 1936
 
2.0%
Other values (101) 46978
48.7%
2025-02-11T20:01:21.351350image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 52512
18.2%
- 37674
13.0%
S 26861
9.3%
D 26835
9.3%
3 23861
8.3%
1 21340
 
7.4%
2 19625
 
6.8%
H 11333
 
3.9%
C 7784
 
2.7%
4 6249
 
2.2%
Other values (30) 54882
19.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 155504
53.8%
Decimal Number 95746
33.1%
Dash Punctuation 37674
 
13.0%
Lowercase Letter 28
 
< 0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 52512
33.8%
S 26861
17.3%
D 26835
17.3%
H 11333
 
7.3%
C 7784
 
5.0%
M 5014
 
3.2%
T 4386
 
2.8%
B 3055
 
2.0%
V 3046
 
2.0%
R 2879
 
1.9%
Other values (9) 11799
 
7.6%
Decimal Number
ValueCountFrequency (%)
3 23861
24.9%
1 21340
22.3%
2 19625
20.5%
4 6249
 
6.5%
7 5566
 
5.8%
5 5137
 
5.4%
6 4440
 
4.6%
8 3284
 
3.4%
0 3207
 
3.3%
9 3037
 
3.2%
Lowercase Letter
ValueCountFrequency (%)
o 6
21.4%
a 6
21.4%
p 4
14.3%
r 2
 
7.1%
u 2
 
7.1%
z 2
 
7.1%
t 2
 
7.1%
c 2
 
7.1%
l 2
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 37674
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 155532
53.8%
Common 133424
46.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 52512
33.8%
S 26861
17.3%
D 26835
17.3%
H 11333
 
7.3%
C 7784
 
5.0%
M 5014
 
3.2%
T 4386
 
2.8%
B 3055
 
2.0%
V 3046
 
2.0%
R 2879
 
1.9%
Other values (18) 11827
 
7.6%
Common
ValueCountFrequency (%)
- 37674
28.2%
3 23861
17.9%
1 21340
16.0%
2 19625
14.7%
4 6249
 
4.7%
7 5566
 
4.2%
5 5137
 
3.9%
6 4440
 
3.3%
8 3284
 
2.5%
0 3207
 
2.4%
Other values (2) 3041
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 52512
18.2%
- 37674
13.0%
S 26861
9.3%
D 26835
9.3%
3 23861
8.3%
1 21340
 
7.4%
2 19625
 
6.8%
H 11333
 
3.9%
C 7784
 
2.7%
4 6249
 
2.2%
Other values (30) 54882
19.0%

Procedencia_direccion
Text

Distinct97
Distinct (%)0.1%
Missing437
Missing (%)0.5%
Memory size756.7 KiB
2025-02-11T20:01:21.509717image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length95
Median length74
Mean length32.238634
Min length2

Characters and Unicode

Total characters3108030
Distinct characters64
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSin datos
2nd rowSin datos
3rd rowSin datos
4th rowSin datos
5th rowSin datos
ValueCountFrequency (%)
col 60703
 
12.9%
ministerio 48754
 
10.4%
público 48754
 
10.4%
sin 26835
 
5.7%
datos 26835
 
5.7%
balbuena 9989
 
2.1%
territorial 9625
 
2.0%
coordinación 9625
 
2.0%
1 8111
 
1.7%
hospital 7871
 
1.7%
Other values (149) 213930
45.4%
2025-02-11T20:01:21.820874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
374625
 
12.1%
i 298705
 
9.6%
o 297107
 
9.6%
a 204152
 
6.6%
l 182274
 
5.9%
n 172098
 
5.5%
r 170709
 
5.5%
e 143069
 
4.6%
t 124593
 
4.0%
s 108133
 
3.5%
Other values (54) 1032565
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2126900
68.4%
Space Separator 374625
 
12.1%
Uppercase Letter 373994
 
12.0%
Decimal Number 99975
 
3.2%
Close Punctuation 64494
 
2.1%
Open Punctuation 64494
 
2.1%
Other Punctuation 2759
 
0.1%
Other Letter 789
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 298705
14.0%
o 297107
14.0%
a 204152
9.6%
l 182274
8.6%
n 172098
8.1%
r 170709
8.0%
e 143069
6.7%
t 124593
 
5.9%
s 108133
 
5.1%
c 88472
 
4.2%
Other values (17) 337588
15.9%
Uppercase Letter
ValueCountFrequency (%)
C 88711
23.7%
M 64456
17.2%
P 56524
15.1%
S 40822
10.9%
T 22677
 
6.1%
B 16559
 
4.4%
A 12383
 
3.3%
G 11974
 
3.2%
H 11955
 
3.2%
V 10642
 
2.8%
Other values (12) 37291
10.0%
Decimal Number
ValueCountFrequency (%)
3 23859
23.9%
2 22141
22.1%
1 21337
21.3%
4 6246
 
6.2%
7 5566
 
5.6%
5 5133
 
5.1%
0 4932
 
4.9%
6 4440
 
4.4%
8 3284
 
3.3%
9 3037
 
3.0%
Space Separator
ValueCountFrequency (%)
374625
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64494
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64494
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2759
100.0%
Other Letter
ValueCountFrequency (%)
ª 789
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2501683
80.5%
Common 606347
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 298705
11.9%
o 297107
11.9%
a 204152
 
8.2%
l 182274
 
7.3%
n 172098
 
6.9%
r 170709
 
6.8%
e 143069
 
5.7%
t 124593
 
5.0%
s 108133
 
4.3%
C 88711
 
3.5%
Other values (40) 712132
28.5%
Common
ValueCountFrequency (%)
374625
61.8%
) 64494
 
10.6%
( 64494
 
10.6%
3 23859
 
3.9%
2 22141
 
3.7%
1 21337
 
3.5%
4 6246
 
1.0%
7 5566
 
0.9%
5 5133
 
0.8%
0 4932
 
0.8%
Other values (4) 13520
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3019464
97.2%
None 88566
 
2.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
374625
 
12.4%
i 298705
 
9.9%
o 297107
 
9.8%
a 204152
 
6.8%
l 182274
 
6.0%
n 172098
 
5.7%
r 170709
 
5.7%
e 143069
 
4.7%
t 124593
 
4.1%
s 108133
 
3.6%
Other values (46) 943999
31.3%
None
ValueCountFrequency (%)
ú 48760
55.1%
ó 16792
 
19.0%
á 8391
 
9.5%
í 6582
 
7.4%
é 5364
 
6.1%
ñ 1295
 
1.5%
ª 789
 
0.9%
Á 593
 
0.7%

Procedencia_alcaldia
Categorical

MISSING 

Distinct16
Distinct (%)< 0.1%
Missing31946
Missing (%)33.0%
Memory size756.7 KiB
Cuauhtémoc
10686 
Miguel Hidalgo
10494 
Gustavo A. Madero
9012 
Benito Juárez
8647 
Venustiano Carranza
7580 
Other values (11)
18479 

Length

Max length19
Median length17
Mean length13.087876
Min length7

Characters and Unicode

Total characters849377
Distinct characters39
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCuauhtémoc
2nd rowCuauhtémoc
3rd rowBenito Juárez
4th rowCoyoacán
5th rowCuauhtémoc

Common Values

ValueCountFrequency (%)
Cuauhtémoc 10686
 
11.0%
Miguel Hidalgo 10494
 
10.8%
Gustavo A. Madero 9012
 
9.3%
Benito Juárez 8647
 
8.9%
Venustiano Carranza 7580
 
7.8%
Iztacalco 4232
 
4.4%
Coyoacán 2638
 
2.7%
Álvaro Obregón 2412
 
2.5%
Iztapalapa 2356
 
2.4%
Azcapotzalco 2203
 
2.3%
Other values (6) 4638
 
4.8%
(Missing) 31946
33.0%

Length

2025-02-11T20:01:21.882850image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cuauhtémoc 10686
9.5%
hidalgo 10494
9.3%
miguel 10494
9.3%
gustavo 9012
8.0%
a 9012
8.0%
madero 9012
8.0%
benito 8647
7.7%
juárez 8647
7.7%
venustiano 7580
 
6.7%
carranza 7580
 
6.7%
Other values (14) 21511
19.1%

Most occurring characters

ValueCountFrequency (%)
a 104873
 
12.3%
o 74416
 
8.8%
u 58358
 
6.9%
47777
 
5.6%
e 47526
 
5.6%
t 45336
 
5.3%
i 40530
 
4.8%
n 38790
 
4.6%
l 38701
 
4.6%
r 38010
 
4.5%
Other values (29) 315060
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 679913
80.0%
Uppercase Letter 112675
 
13.3%
Space Separator 47777
 
5.6%
Other Punctuation 9012
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 104873
15.4%
o 74416
10.9%
u 58358
 
8.6%
e 47526
 
7.0%
t 45336
 
6.7%
i 40530
 
6.0%
n 38790
 
5.7%
l 38701
 
5.7%
r 38010
 
5.6%
c 28969
 
4.3%
Other values (14) 164404
24.2%
Uppercase Letter
ValueCountFrequency (%)
C 22041
19.6%
M 20126
17.9%
A 11468
10.2%
H 10494
9.3%
G 9012
8.0%
J 8647
 
7.7%
B 8647
 
7.7%
V 7580
 
6.7%
I 6588
 
5.8%
O 2412
 
2.1%
Other values (3) 5660
 
5.0%
Space Separator
ValueCountFrequency (%)
47777
100.0%
Other Punctuation
ValueCountFrequency (%)
. 9012
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 792588
93.3%
Common 56789
 
6.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 104873
 
13.2%
o 74416
 
9.4%
u 58358
 
7.4%
e 47526
 
6.0%
t 45336
 
5.7%
i 40530
 
5.1%
n 38790
 
4.9%
l 38701
 
4.9%
r 38010
 
4.8%
c 28969
 
3.7%
Other values (27) 277079
35.0%
Common
ValueCountFrequency (%)
47777
84.1%
. 9012
 
15.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 822099
96.8%
None 27278
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 104873
 
12.8%
o 74416
 
9.1%
u 58358
 
7.1%
47777
 
5.8%
e 47526
 
5.8%
t 45336
 
5.5%
i 40530
 
4.9%
n 38790
 
4.7%
l 38701
 
4.7%
r 38010
 
4.6%
Other values (25) 287782
35.0%
None
ValueCountFrequency (%)
á 11768
43.1%
é 10686
39.2%
ó 2412
 
8.8%
Á 2412
 
8.8%

Numero_acta_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Procedencia_acta
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing25635
Missing (%)26.5%
Memory size756.7 KiB

Diagnostico_transcrito
Text

Distinct3709
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
2025-02-11T20:01:21.998474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length43
Median length3
Mean length3.5325059
Min length1

Characters and Unicode

Total characters342102
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2805 ?
Unique (%)2.9%

Sample

1st rowS-D
2nd rowS-D
3rd rowS-D
4th rowS-D
5th rowS-D
ValueCountFrequency (%)
s-d 55880
56.6%
tm 7526
 
7.6%
tce 6010
 
6.1%
bn 1906
 
1.9%
cvg 1306
 
1.3%
tct 1182
 
1.2%
dispensa 844
 
0.9%
hpafpc 835
 
0.8%
aova 804
 
0.8%
quemaduras 762
 
0.8%
Other values (3215) 21726
 
22.0%
2025-02-11T20:01:22.185807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 57783
16.9%
D 56974
16.7%
- 55897
16.3%
T 26375
 
7.7%
C 17770
 
5.2%
A 12181
 
3.6%
P 11212
 
3.3%
M 9882
 
2.9%
E 9265
 
2.7%
N 7975
 
2.3%
Other values (64) 76788
22.4%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 239529
70.0%
Dash Punctuation 55897
 
16.3%
Lowercase Letter 38116
 
11.1%
Math Symbol 6093
 
1.8%
Space Separator 1937
 
0.6%
Other Punctuation 450
 
0.1%
Open Punctuation 28
 
< 0.1%
Decimal Number 27
 
< 0.1%
Close Punctuation 25
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 57783
24.1%
D 56974
23.8%
T 26375
11.0%
C 17770
 
7.4%
A 12181
 
5.1%
P 11212
 
4.7%
M 9882
 
4.1%
E 9265
 
3.9%
N 7975
 
3.3%
H 6757
 
2.8%
Other values (16) 23355
9.8%
Lowercase Letter
ValueCountFrequency (%)
s 5216
13.7%
e 4795
12.6%
a 3988
10.5%
n 2887
 
7.6%
r 2720
 
7.1%
u 2719
 
7.1%
i 2563
 
6.7%
o 1890
 
5.0%
m 1796
 
4.7%
x 1688
 
4.4%
Other values (15) 7854
20.6%
Other Punctuation
ValueCountFrequency (%)
. 377
83.8%
? 23
 
5.1%
" 19
 
4.2%
/ 19
 
4.2%
' 6
 
1.3%
, 3
 
0.7%
: 2
 
0.4%
* 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 18
66.7%
4 3
 
11.1%
9 2
 
7.4%
6 1
 
3.7%
1 1
 
3.7%
5 1
 
3.7%
3 1
 
3.7%
Math Symbol
ValueCountFrequency (%)
+ 6092
> 99.9%
= 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 15
53.6%
[ 13
46.4%
Close Punctuation
ValueCountFrequency (%)
] 13
52.0%
) 12
48.0%
Dash Punctuation
ValueCountFrequency (%)
- 55897
100.0%
Space Separator
ValueCountFrequency (%)
1937
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 277645
81.2%
Common 64457
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 57783
20.8%
D 56974
20.5%
T 26375
9.5%
C 17770
 
6.4%
A 12181
 
4.4%
P 11212
 
4.0%
M 9882
 
3.6%
E 9265
 
3.3%
N 7975
 
2.9%
H 6757
 
2.4%
Other values (41) 61471
22.1%
Common
ValueCountFrequency (%)
- 55897
86.7%
+ 6092
 
9.5%
1937
 
3.0%
. 377
 
0.6%
? 23
 
< 0.1%
" 19
 
< 0.1%
/ 19
 
< 0.1%
2 18
 
< 0.1%
( 15
 
< 0.1%
] 13
 
< 0.1%
Other values (13) 47
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 342102
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 57783
16.9%
D 56974
16.7%
- 55897
16.3%
T 26375
 
7.7%
C 17770
 
5.2%
A 12181
 
3.6%
P 11212
 
3.3%
M 9882
 
2.9%
E 9265
 
2.7%
N 7975
 
2.3%
Other values (64) 76788
22.4%

Diagnostico_estandar
Text

MISSING 

Distinct108
Distinct (%)0.1%
Missing8267
Missing (%)8.5%
Memory size756.7 KiB
2025-02-11T20:01:22.308536image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length15
Median length3
Mean length3.1212391
Min length1

Characters and Unicode

Total characters276470
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowS-D
2nd rowS-D
3rd rowS-D
4th rowS-D
5th rowS-D
ValueCountFrequency (%)
s-d 55895
63.1%
tm 7513
 
8.5%
tce 5951
 
6.7%
bn 1859
 
2.1%
cvg 1291
 
1.5%
tct 1177
 
1.3%
hpaf 954
 
1.1%
dispensa 918
 
1.0%
hpafpc 896
 
1.0%
aova 802
 
0.9%
Other values (100) 11362
 
12.8%
2025-02-11T20:01:22.481351image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 59139
21.4%
D 57006
20.6%
- 55895
20.2%
T 22573
 
8.2%
C 13836
 
5.0%
A 11151
 
4.0%
E 9995
 
3.6%
M 9299
 
3.4%
P 8555
 
3.1%
N 4940
 
1.8%
Other values (15) 24081
8.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 220529
79.8%
Dash Punctuation 55895
 
20.2%
Space Separator 41
 
< 0.1%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 59139
26.8%
D 57006
25.8%
T 22573
 
10.2%
C 13836
 
6.3%
A 11151
 
5.1%
E 9995
 
4.5%
M 9299
 
4.2%
P 8555
 
3.9%
N 4940
 
2.2%
H 4240
 
1.9%
Other values (12) 19795
 
9.0%
Dash Punctuation
ValueCountFrequency (%)
- 55895
100.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Decimal Number
ValueCountFrequency (%)
2 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 220529
79.8%
Common 55941
 
20.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 59139
26.8%
D 57006
25.8%
T 22573
 
10.2%
C 13836
 
6.3%
A 11151
 
5.1%
E 9995
 
4.5%
M 9299
 
4.2%
P 8555
 
3.9%
N 4940
 
2.2%
H 4240
 
1.9%
Other values (12) 19795
 
9.0%
Common
ValueCountFrequency (%)
- 55895
99.9%
41
 
0.1%
2 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 276470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 59139
21.4%
D 57006
20.6%
- 55895
20.2%
T 22573
 
8.2%
C 13836
 
5.0%
A 11151
 
4.0%
E 9995
 
3.6%
M 9299
 
3.4%
P 8555
 
3.1%
N 4940
 
1.8%
Other values (15) 24081
8.7%

Diagnostico_extendido
Text

MISSING 

Distinct95
Distinct (%)0.1%
Missing8267
Missing (%)8.5%
Memory size756.7 KiB
2025-02-11T20:01:22.599046image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Length

Max length48
Median length9
Mean length14.288483
Min length5

Characters and Unicode

Total characters1265631
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowsin datos
2nd rowsin datos
3rd rowsin datos
4th rowsin datos
5th rowsin datos
ValueCountFrequency (%)
sin 55895
27.9%
datos 55895
27.9%
traumatismo 18218
 
9.1%
craneo 9132
 
4.6%
multiple 7513
 
3.8%
encefalico 6049
 
3.0%
herida 3656
 
1.8%
torax 3571
 
1.8%
fuego 3026
 
1.5%
arma 3026
 
1.5%
Other values (91) 34137
17.1%
2025-02-11T20:01:22.768892image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 153991
12.2%
s 145022
11.5%
o 122268
9.7%
i 114315
9.0%
t 111748
8.8%
111541
8.8%
n 95228
7.5%
d 68814
 
5.4%
e 62608
 
4.9%
r 58260
 
4.6%
Other values (15) 221836
17.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1154085
91.2%
Space Separator 111541
 
8.8%
Decimal Number 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 153991
13.3%
s 145022
12.6%
o 122268
10.6%
i 114315
9.9%
t 111748
9.7%
n 95228
8.3%
d 68814
6.0%
e 62608
 
5.4%
r 58260
 
5.0%
m 57531
 
5.0%
Other values (13) 164300
14.2%
Space Separator
ValueCountFrequency (%)
111541
100.0%
Decimal Number
ValueCountFrequency (%)
2 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1154085
91.2%
Common 111546
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 153991
13.3%
s 145022
12.6%
o 122268
10.6%
i 114315
9.9%
t 111748
9.7%
n 95228
8.3%
d 68814
6.0%
e 62608
 
5.4%
r 58260
 
5.0%
m 57531
 
5.0%
Other values (13) 164300
14.2%
Common
ValueCountFrequency (%)
111541
> 99.9%
2 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1265631
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 153991
12.2%
s 145022
11.5%
o 122268
9.7%
i 114315
9.0%
t 111748
8.8%
111541
8.8%
n 95228
7.5%
d 68814
 
5.4%
e 62608
 
4.9%
r 58260
 
4.6%
Other values (15) 221836
17.5%

Sexo
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
Masculino
73741 
Femenino
20601 
S-D
 
2502

Length

Max length9
Median length9
Mean length8.6322643
Min length3

Characters and Unicode

Total characters835983
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemenino
2nd rowFemenino
3rd rowMasculino
4th rowMasculino
5th rowFemenino

Common Values

ValueCountFrequency (%)
Masculino 73741
76.1%
Femenino 20601
 
21.3%
S-D 2502
 
2.6%

Length

2025-02-11T20:01:22.828310image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-11T20:01:22.874517image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
masculino 73741
76.1%
femenino 20601
 
21.3%
s-d 2502
 
2.6%

Most occurring characters

ValueCountFrequency (%)
n 114943
13.7%
i 94342
11.3%
o 94342
11.3%
M 73741
8.8%
a 73741
8.8%
s 73741
8.8%
c 73741
8.8%
u 73741
8.8%
l 73741
8.8%
e 41202
 
4.9%
Other values (5) 48708
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 734135
87.8%
Uppercase Letter 99346
 
11.9%
Dash Punctuation 2502
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 114943
15.7%
i 94342
12.9%
o 94342
12.9%
a 73741
10.0%
s 73741
10.0%
c 73741
10.0%
u 73741
10.0%
l 73741
10.0%
e 41202
 
5.6%
m 20601
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
M 73741
74.2%
F 20601
 
20.7%
S 2502
 
2.5%
D 2502
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 2502
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 833481
99.7%
Common 2502
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 114943
13.8%
i 94342
11.3%
o 94342
11.3%
M 73741
8.8%
a 73741
8.8%
s 73741
8.8%
c 73741
8.8%
u 73741
8.8%
l 73741
8.8%
e 41202
 
4.9%
Other values (4) 46206
5.5%
Common
ValueCountFrequency (%)
- 2502
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 835983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 114943
13.7%
i 94342
11.3%
o 94342
11.3%
M 73741
8.8%
a 73741
8.8%
s 73741
8.8%
c 73741
8.8%
u 73741
8.8%
l 73741
8.8%
e 41202
 
4.9%
Other values (5) 48708
5.8%

Edad_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Tipo_restos
Categorical

IMBALANCE 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
Cadáver
91254 
Feto
 
2844
Miembros
 
2065
Recién nacido
 
633
Restos óseos
 
48

Length

Max length13
Median length7
Mean length6.9749184
Min length4

Characters and Unicode

Total characters675479
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCadáver
2nd rowCadáver
3rd rowCadáver
4th rowCadáver
5th rowCadáver

Common Values

ValueCountFrequency (%)
Cadáver 91254
94.2%
Feto 2844
 
2.9%
Miembros 2065
 
2.1%
Recién nacido 633
 
0.7%
Restos óseos 48
 
< 0.1%

Length

2025-02-11T20:01:22.910584image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-11T20:01:22.951596image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
cadáver 91254
93.6%
feto 2844
 
2.9%
miembros 2065
 
2.1%
recién 633
 
0.6%
nacido 633
 
0.6%
restos 48
 
< 0.1%
óseos 48
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 96892
14.3%
r 93319
13.8%
d 91887
13.6%
a 91887
13.6%
C 91254
13.5%
á 91254
13.5%
v 91254
13.5%
o 5638
 
0.8%
i 3331
 
0.5%
t 2892
 
0.4%
Other values (11) 15871
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 577954
85.6%
Uppercase Letter 96844
 
14.3%
Space Separator 681
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 96892
16.8%
r 93319
16.1%
d 91887
15.9%
a 91887
15.9%
á 91254
15.8%
v 91254
15.8%
o 5638
 
1.0%
i 3331
 
0.6%
t 2892
 
0.5%
s 2257
 
0.4%
Other values (6) 7343
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
C 91254
94.2%
F 2844
 
2.9%
M 2065
 
2.1%
R 681
 
0.7%
Space Separator
ValueCountFrequency (%)
681
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 674798
99.9%
Common 681
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 96892
14.4%
r 93319
13.8%
d 91887
13.6%
a 91887
13.6%
C 91254
13.5%
á 91254
13.5%
v 91254
13.5%
o 5638
 
0.8%
i 3331
 
0.5%
t 2892
 
0.4%
Other values (10) 15190
 
2.3%
Common
ValueCountFrequency (%)
681
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 583544
86.4%
None 91935
 
13.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 96892
16.6%
r 93319
16.0%
d 91887
15.7%
a 91887
15.7%
C 91254
15.6%
v 91254
15.6%
o 5638
 
1.0%
i 3331
 
0.6%
t 2892
 
0.5%
F 2844
 
0.5%
Other values (8) 12346
 
2.1%
None
ValueCountFrequency (%)
á 91254
99.3%
é 633
 
0.7%
ó 48
 
0.1%

Bitacora_ingresos
Categorical

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
semefo_df_bo_1981
7629 
semefo_df_bo_1980
7619 
semefo_df_bo_1982
7493 
semefo_df_bo_1979
7461 
semefo_df_bo_1977
7166 
Other values (10)
59476 

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters1646348
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsemefo_df_bo_1968
2nd rowsemefo_df_bo_1968
3rd rowsemefo_df_bo_1968
4th rowsemefo_df_bo_1968
5th rowsemefo_df_bo_1968

Common Values

ValueCountFrequency (%)
semefo_df_bo_1981 7629
 
7.9%
semefo_df_bo_1980 7619
 
7.9%
semefo_df_bo_1982 7493
 
7.7%
semefo_df_bo_1979 7461
 
7.7%
semefo_df_bo_1977 7166
 
7.4%
semefo_df_bo_1978 7140
 
7.4%
semefo_df_bo_1976 6907
 
7.1%
semefo_df_bo_1975 6861
 
7.1%
semefo_df_bo_1973 6471
 
6.7%
semefo_df_bo_1972 5768
 
6.0%
Other values (5) 26329
27.2%

Length

2025-02-11T20:01:22.989846image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
semefo_df_bo_1981 7629
 
7.9%
semefo_df_bo_1980 7619
 
7.9%
semefo_df_bo_1982 7493
 
7.7%
semefo_df_bo_1979 7461
 
7.7%
semefo_df_bo_1977 7166
 
7.4%
semefo_df_bo_1978 7140
 
7.4%
semefo_df_bo_1976 6907
 
7.1%
semefo_df_bo_1975 6861
 
7.1%
semefo_df_bo_1973 6471
 
6.7%
semefo_df_bo_1972 5768
 
6.0%
Other values (5) 26329
27.2%

Most occurring characters

ValueCountFrequency (%)
_ 290532
17.6%
e 193688
11.8%
f 193688
11.8%
o 193688
11.8%
1 109997
 
6.7%
9 109357
 
6.6%
b 96844
 
5.9%
s 96844
 
5.9%
d 96844
 
5.9%
m 96844
 
5.9%
Other values (8) 168022
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 968440
58.8%
Decimal Number 387376
 
23.5%
Connector Punctuation 290532
 
17.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 109997
28.4%
9 109357
28.2%
7 71498
18.5%
8 34600
 
8.9%
6 16678
 
4.3%
2 13261
 
3.4%
0 12922
 
3.3%
5 6861
 
1.8%
3 6471
 
1.7%
4 5731
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
e 193688
20.0%
f 193688
20.0%
o 193688
20.0%
b 96844
10.0%
s 96844
10.0%
d 96844
10.0%
m 96844
10.0%
Connector Punctuation
ValueCountFrequency (%)
_ 290532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 968440
58.8%
Common 677908
41.2%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 290532
42.9%
1 109997
 
16.2%
9 109357
 
16.1%
7 71498
 
10.5%
8 34600
 
5.1%
6 16678
 
2.5%
2 13261
 
2.0%
0 12922
 
1.9%
5 6861
 
1.0%
3 6471
 
1.0%
Latin
ValueCountFrequency (%)
e 193688
20.0%
f 193688
20.0%
o 193688
20.0%
b 96844
10.0%
s 96844
10.0%
d 96844
10.0%
m 96844
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1646348
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 290532
17.6%
e 193688
11.8%
f 193688
11.8%
o 193688
11.8%
1 109997
 
6.7%
9 109357
 
6.6%
b 96844
 
5.9%
s 96844
 
5.9%
d 96844
 
5.9%
m 96844
 
5.9%
Other values (8) 168022
10.2%

Pagina_PDF
Real number (ℝ)

Distinct260
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.24627
Minimum2
Maximum261
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size756.7 KiB
2025-02-11T20:01:23.036197image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile12
Q153
median104
Q3156
95-th percentile226
Maximum261
Range259
Interquartile range (IQR)103

Descriptive statistics

Standard deviation65.798085
Coefficient of variation (CV)0.60785543
Kurtosis-0.86945586
Mean108.24627
Median Absolute Deviation (MAD)52
Skewness0.29364454
Sum10483002
Variance4329.388
MonotonicityNot monotonic
2025-02-11T20:01:23.090116image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 524
 
0.5%
123 520
 
0.5%
103 519
 
0.5%
63 516
 
0.5%
108 515
 
0.5%
119 515
 
0.5%
28 515
 
0.5%
5 514
 
0.5%
107 514
 
0.5%
61 514
 
0.5%
Other values (250) 91678
94.7%
ValueCountFrequency (%)
2 68
 
0.1%
3 443
0.5%
4 513
0.5%
5 514
0.5%
6 513
0.5%
7 512
0.5%
8 473
0.5%
9 486
0.5%
10 452
0.5%
11 512
0.5%
ValueCountFrequency (%)
261 4
 
< 0.1%
260 22
 
< 0.1%
259 34
 
< 0.1%
258 36
 
< 0.1%
257 34
 
< 0.1%
256 61
0.1%
255 76
0.1%
254 90
0.1%
253 135
0.1%
252 114
0.1%

Foja_transcrito
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size756.7 KiB

Observaciones
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing82723
Missing (%)85.4%
Memory size756.7 KiB

Conocido_desconocido
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size756.7 KiB
conocido
78613 
desconocido
18212 
S-D
 
19

Length

Max length11
Median length8
Mean length8.5631841
Min length3

Characters and Unicode

Total characters829293
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowconocido
2nd rowconocido
3rd rowconocido
4th rowconocido
5th rowconocido

Common Values

ValueCountFrequency (%)
conocido 78613
81.2%
desconocido 18212
 
18.8%
S-D 19
 
< 0.1%

Length

2025-02-11T20:01:23.139970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-11T20:01:23.182474image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
conocido 78613
81.2%
desconocido 18212
 
18.8%
s-d 19
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
o 290475
35.0%
c 193650
23.4%
d 115037
 
13.9%
n 96825
 
11.7%
i 96825
 
11.7%
e 18212
 
2.2%
s 18212
 
2.2%
S 19
 
< 0.1%
- 19
 
< 0.1%
D 19
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 829236
> 99.9%
Uppercase Letter 38
 
< 0.1%
Dash Punctuation 19
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 290475
35.0%
c 193650
23.4%
d 115037
 
13.9%
n 96825
 
11.7%
i 96825
 
11.7%
e 18212
 
2.2%
s 18212
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
S 19
50.0%
D 19
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 829274
> 99.9%
Common 19
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 290475
35.0%
c 193650
23.4%
d 115037
 
13.9%
n 96825
 
11.7%
i 96825
 
11.7%
e 18212
 
2.2%
s 18212
 
2.2%
S 19
 
< 0.1%
D 19
 
< 0.1%
Common
ValueCountFrequency (%)
- 19
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 829293
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 290475
35.0%
c 193650
23.4%
d 115037
 
13.9%
n 96825
 
11.7%
i 96825
 
11.7%
e 18212
 
2.2%
s 18212
 
2.2%
S 19
 
< 0.1%
- 19
 
< 0.1%
D 19
 
< 0.1%

Interactions

2025-02-11T20:01:18.141065image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Correlations

2025-02-11T20:01:23.215411image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Bitacora_ingresosConocido_desconocidoPagina_PDFProcedencia_alcaldiaSexoTipo_restos
Bitacora_ingresos1.0000.0470.2170.0730.1010.042
Conocido_desconocido0.0471.0000.3030.1720.1930.279
Pagina_PDF0.2170.3031.0000.0330.1300.287
Procedencia_alcaldia0.0730.1720.0331.0000.0510.059
Sexo0.1010.1930.1300.0511.0000.460
Tipo_restos0.0420.2790.2870.0590.4601.000

Missing values

2025-02-11T20:01:18.303606image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-11T20:01:18.595496image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-11T20:01:18.916169image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoObservacionesConocido_desconocido
0BO_1968_00001S-Dacosta ortega teresaacostaortegateresa1968-01-03 00:00:001968-01-0337S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoS-DCadáversemefo_df_bo_196821NaNconocido
1BO_1968_00002S-Davila de cuestas catalinaavilade cuestascatalina1968-01-05 00:00:001968-01-0558S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoS-DCadáversemefo_df_bo_196821NaNconocido
2BO_1968_00003S-Darzate paredes juanarzateparedesjuan1968-01-07 00:00:001968-01-0783S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
3BO_1968_00004S-Dalvarez martinez isaacalvarezmartinezisaac1968-01-07 00:00:001968-01-0786S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
4BO_1968_00005S-Darellano viuda de campos ma.arellanoviuda de camposma.1968-01-07 00:00:001968-01-0788S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosFemeninoS-DCadáversemefo_df_bo_196821NaNconocido
5BO_1968_00006S-Darce macedo justoarcemacedojusto1968-01-09 00:00:001968-01-09115S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
6BO_1968_00007S-Dalvarez vela jesusalvarezvelajesus1968-01-02 00:00:001968-01-0222S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
7BO_1968_00008S-Davila ramirez pabloavilaramirezpablo1968-01-10 00:00:001968-01-10137S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
8BO_1968_00009S-Dalvarado aurelioalvarados-daurelio1968-01-10 00:00:001968-01-10139S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
9BO_1968_00010S-Dalvarez almaguer arturoalvarezalmaguerarturo1968-01-10 00:00:001968-01-10132S-DS-DSin datosNaNS-DNaNS-DS-Dsin datosMasculinoS-DCadáversemefo_df_bo_196821NaNconocido
IDNumero_progresivo_transcritoNombre_completo_transcritoPrimer_apellidoSegundo_apellidoNombres_propiosFecha_transcritoFecha_estandarExpediente_SEMEFO_transcritoProcedencia_transcritoProcedencia_estandarProcedencia_direccionProcedencia_alcaldiaNumero_acta_transcritoProcedencia_actaDiagnostico_transcritoDiagnostico_estandarDiagnostico_extendidoSexoEdad_transcritoTipo_restosBitacora_ingresosPagina_PDFFoja_transcritoObservacionesConocido_desconocido
96834BO_1982_07484S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-10-27 00:00:001982-10-27604032a32AMinisterio Público 32NaN142332a -- 1423S-DS-Dsin datosMasculinoS-DMiembrossemefo_df_bo_1982250155punto rojo en expediente_semefo y raya roja en procedencia. no copias rlconocido
96835BO_1982_07485S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-10-27 00:00:001982-10-27604134a34AMinisterio Público 34 (Col Santo Tomás)Miguel Hidalgo145434a -- 1454S-DS-Dsin datosMasculinoS-DMiembrossemefo_df_bo_1982250155punto rojo en expediente_semefo y raya roja en procedenciaconocido
96836BO_1982_07486S-DNombre de particular que podría encontrarse con vida. Se clasifica como confidencial con fundamento en el artículo 116 de la LGTAIP.NaNs-dNaN1982-03-11 00:00:001982-03-11145337a37AMinisterio Público 37 (Col Polanco)Miguel Hidalgo22437a -- 224S-DS-Dsin datosMasculinoS-DMiembrossemefo_df_bo_1982251156NaNconocido
96837BO_1982_07487S-Drestos placentarioss-ds-ds-d1982-06-10 00:00:001982-06-1032588a8AMinisterio Público 8 (Col Narvarte)Benito Juárez18038a -- 1803S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96838BO_1982_07488S-Drestos humanos de desconocidos-ds-ds-d1982-05-03 00:00:001982-05-03110023a23AMinisterio Público 23 (Col La Joya Tlalpan)Tlalpan40523a -- 405S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96839BO_1982_07489S-Dplacentas-ds-ds-d1982-06-05 00:00:001982-06-05307915a15AMinisterio Público 15 (Col Aragón La Villa)Gustavo A. Madero96015a -- 960S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96840BO_1982_07490S-D5 dedos del pie derecho de desconocidos-ds-ds-d1982-06-05 00:00:001982-06-05306032a32AMinisterio Público 32NaN95032a -- 950S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96841BO_1982_07491S-Ddedo de desconocidos-ds-ds-d1982-11-19 00:00:001982-11-19638932a32AMinisterio Público 32NaN200532a -- 2005S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96842BO_1982_07492S-D4 dedos de desconocidos-ds-ds-d1982-11-28 00:00:001982-11-28652827a27AMinisterio Público 27 (San Pedro)Xochimilco95927a -- 959S-DS-Dsin datosS-DS-DMiembrossemefo_df_bo_1982251156NaNdesconocido
96843BO_1982_07493S-Dosamenta de desconocidos-ds-ds-d1982-10-11 00:00:001982-10-1156299a9AMinisterio Público 9 (Col Tacuba)Miguel Hidalgo41939a -- 4193S-DS-Dsin datosS-DS-DCadáversemefo_df_bo_1982251156no se recibio necropsia. es una osamenta.desconocido